Search results for: health problems.

Authors: Nicholas Milburn, Yu Liang, Dalei Wu

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Athlete performance scoring within the climbing domain presents interesting challenges as the sport does not have an objective way to assign skill. Assessing skill levels within any sport is valuable as it can be used to mark progress while training, and it can help an athlete choose appropriate climbs to attempt. Machine learning-based methods are popular for complex problems like this. The dataset available was composed of dynamic force data recorded during climbing; however, this dataset came with challenges such as data scarcity, imbalance, and it was temporally heterogeneous. Investigated solutions to these challenges include data augmentation, temporal normalization, conversion of time series to the spectral domain, and cross validation strategies. The investigated solutions to the classification problem included light weight machine classifiers KNN and SVM as well as the deep learning with CNN. The best performing model had an 80% accuracy. In conclusion, there seems to be enough information within climbing force data to accurately categorize climbers by skill.

Keywords: Classification, climbing, data imbalance, data scarcity, machine learning, time sequence.

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Authors: Patrick B. Cobbinah, Clifford Amoako

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Kumasi is Ghana’s second largest and fastest growing city with an annual population growth rate of 5.4 percent. A major result of this phenomenon is a growing sprawl at the fringes of the city. This paper assesses the nature, extent and impact of sprawl on Kumasi and examines urban planning efforts at addressing this phenomenon. Both secondary and empirical data were collected from decentralized government departments of the Kumasi Metropolitan Assembly and residents of some sprawling communities. The study reveals that sprawl in the metropolis is rapidly consuming fringe rural communities. This situation has weakened effective management of the metropolis causing problems such as congestion and conversion of peri-urban land into residential use without ancillary infrastructure and social services. The paper recommends effective and timely planning and provision of services as well as an overall economic development and spatial integration through regional planning as a way of achieving a long term solution to sprawl.

Keywords: Kumasi, peri-urban, urban planning, urban sprawl.

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Authors: R. N. Patel

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This paper deals with the tuning of parameters for Automatic Generation Control (AGC). A two area interconnected hydrothermal system with PI controller is considered. Genetic Algorithm (GA) and Particle Swarm optimization (PSO) algorithms have been applied to optimize the controller parameters. Two objective functions namely Integral Square Error (ISE) and Integral of Time-multiplied Absolute value of the Error (ITAE) are considered for optimization. The effectiveness of an objective function is considered based on the variation in tie line power and change in frequency in both the areas. MATLAB/SIMULINK was used as a simulation tool. Simulation results reveal that ITAE is a better objective function than ISE. Performances of optimization algorithms are also compared and it was found that genetic algorithm gives better results than particle swarm optimization algorithm for the problems of AGC.

Keywords: Area control error, Artificial intelligence, Automatic generation control, Genetic Algorithms and modeling, ISE, ITAE, Particle swarm optimization.

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Authors: Konghe Xie

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Two consensus problems are considered in this paper. One is the consensus of linear multi-agent systems with weakly connected directed communication topology. The other is the consensus of nonlinear multi-agent systems with strongly connected directed communication topology. For the first problem, a simplified consensus protocol is designed: Each child agent can only communicate with one of its neighbors. That is, the real communication topology is a directed spanning tree of the original communication topology and without any cycles. Then, the necessary and sufficient condition is put forward to the multi-agent systems can be reached consensus. It is worth noting that the given conditions do not need any eigenvalue of the corresponding Laplacian matrix of the original directed communication network. For the second problem, the feedback gain is designed in the nonlinear consensus protocol. Then, the sufficient condition is proposed such that the systems can be achieved consensus. Besides, the consensus interval is introduced and analyzed to solve the consensus problem. Finally, two numerical simulations are included to verify the theoretical analysis.

Keywords: Consensus, multi-agent systems, directed spanning tree, the Laplacian matrix.

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Authors: S. Sarumathi, M. Vaishnavi, S. Geetha, P. Ranjetha

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Machine learning is a new and exciting area of artificial intelligence nowadays. Machine learning is the most valuable, time, supervised, and cost-effective approach. It is not a narrow learning approach; it also includes a wide range of methods and techniques that can be applied to a wide range of complex realworld problems and time domains. Biological image classification, adaptive testing, computer vision, natural language processing, object detection, cancer detection, face recognition, handwriting recognition, speech recognition, and many other applications of machine learning are widely used in research, industry, and government. Every day, more data are generated, and conventional machine learning techniques are becoming obsolete as users move to distributed and real-time operations. By providing fundamental knowledge of machine learning tools and research opportunities in the field, the aim of this article is to serve as both a comprehensive overview and a guide. A diverse set of machine learning resources is demonstrated and contrasted with the key features in this survey.

Keywords: Artificial intelligence, machine learning, deep learning, machine learning algorithms, machine learning tools.

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Authors: Rania A. Abul Seoud, Nahed H. Solouma, Abou-Baker M. Youssef, Yasser M. Kadah

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Due to the ever growing amount of publications about protein-protein interactions, information extraction from text is increasingly recognized as one of crucial technologies in bioinformatics. This paper presents a Protein Interaction Extraction System using a Link Grammar Parser from biomedical abstracts (PIELG). PIELG uses linkage given by the Link Grammar Parser to start a case based analysis of contents of various syntactic roles as well as their linguistically significant and meaningful combinations. The system uses phrasal-prepositional verbs patterns to overcome preposition combinations problems. The recall and precision are 74.4% and 62.65%, respectively. Experimental evaluations with two other state-of-the-art extraction systems indicate that PIELG system achieves better performance. For further evaluation, the system is augmented with a graphical package (Cytoscape) for extracting protein interaction information from sequence databases. The result shows that the performance is remarkably promising.

Keywords: Link Grammar Parser, Interaction extraction, protein-protein interaction, Natural language processing.

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Authors: Daniel Rivero, Julián Dorado, Juan R. Rabuñal, Alejandro Pazos, Javier Pereira

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The development of Artificial Neural Networks (ANNs) is usually a slow process in which the human expert has to test several architectures until he finds the one that achieves best results to solve a certain problem. This work presents a new technique that uses Genetic Programming (GP) for automatically generating ANNs. To do this, the GP algorithm had to be changed in order to work with graph structures, so ANNs can be developed. This technique also allows the obtaining of simplified networks that solve the problem with a small group of neurons. In order to measure the performance of the system and to compare the results with other ANN development methods by means of Evolutionary Computation (EC) techniques, several tests were performed with problems based on some of the most used test databases. The results of those comparisons show that the system achieves good results comparable with the already existing techniques and, in most of the cases, they worked better than those techniques.

Keywords: Artificial Neural Networks, Evolutionary Computation, Genetic Programming.

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Authors: Kostyantyn Yermashov, Karsten Wolke, Karl Hayo Siemsen

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Domain-specific languages describe specific solutions to problems in the application domain. Traditionally they form a solution composing black-box abstractions together. This, usually, involves non-deep transformations over the target model. In this paper we argue that it is potentially powerful to operate with grey-box abstractions to build a domain-specific software system. We present parametric code templates as grey-box abstractions and conceptual tools to encapsulate and manipulate these templates. Manipulations introduce template-s merging routines and can be defined in a generic way. This involves reasoning mechanisms at the code templates level. We introduce the concept of Neurath Modelling Language (NML) that operates with parametric code templates and specifies a visualisation mapping mechanism for target models. Finally we provide an example of calculating a domain-specific software system with predefined NML elements.

Keywords: software design, code templates, domain-specific languages, modelling languages, generic tools

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Authors: Ali A. Alshatwi, Vaiyapuri S. Periasamy, Jegan Athinarayanan

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Engineered nanoparticles’ usage rapidly increased in various applications in the last decade due to their unusual properties. However, there is an ever increasing concern to understand their toxicological effect in human health. Particularly, metal and metal oxide nanoparticles have been used in various sectors including biomedical, food and agriculture. But their impact on human health is yet to be fully understood. In this present investigation, we assessed the toxic effect of engineered nanoparticles (ENPs) including Ag, MgO and Co3O4 nanoparticles (NPs) on human mesenchymal stem cells (hMSC) adopting cell viability and cellular morphological changes as tools The results suggested that silver NPs are more toxic than MgO and Co3O4NPs. The ENPs induced cytotoxicity and nuclear morphological changes in hMSC depending on dose. The cell viability decreases with increase in concentration of ENPs. The cellular morphology studies revealed that ENPs damaged the cells. These preliminary findings have implications for the use of these nanoparticles in food industry with systematic regulations.

Keywords: Cobalt oxide, Human mesenchymal stem cells, MgO, Silver.

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Authors: Elia Favarelli, Enrico Testi, Andrea Giorgetti

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Autonomous structural health monitoring (SHM) of many structures and bridges became a topic of paramount importance for maintenance purposes and safety reasons. This paper proposes a set of machine learning (ML) tools to perform automatic feature selection and detection of anomalies in a bridge from vibrational data and compare different feature extraction schemes to increase the accuracy and reduce the amount of data collected. As a case study, the Z-24 bridge is considered because of the extensive database of accelerometric data in both standard and damaged conditions. The proposed framework starts from the first four fundamental frequencies extracted through operational modal analysis (OMA) and clustering, followed by time-domain filtering (tracking). The fundamental frequencies extracted are then fed to a dimensionality reduction block implemented through two different approaches: feature selection (intelligent multiplexer) that tries to estimate the most reliable frequencies based on the evaluation of some statistical features (i.e., entropy, variance, kurtosis), and feature extraction (auto-associative neural network (ANN)) that combine the fundamental frequencies to extract new damage sensitive features in a low dimensional feature space. Finally, one-class classification (OCC) algorithms perform anomaly detection, trained with standard condition points, and tested with normal and anomaly ones. In particular, principal component analysis (PCA), kernel principal component analysis (KPCA), and autoassociative neural network (ANN) are presented and their performance are compared. It is also shown that, by evaluating the correct features, the anomaly can be detected with accuracy and an F1 score greater than 95%.

Keywords: Anomaly detection, dimensionality reduction, frequencies selection, modal analysis, neural network, structural health monitoring, vibration measurement.

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Authors: Cyrille Lambert, Tatiana Kalganova, Emanuele Stomeo

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Since 1992, year where Hugo de Garis has published the first paper on Evolvable Hardware (EHW), a period of intense creativity has followed. It has been actively researched, developed and applied to various problems. Different approaches have been proposed that created three main classifications: extrinsic, mixtrinsic and intrinsic EHW. Each of these solutions has a real interest. Nevertheless, although the extrinsic evolution generates some excellent results, the intrinsic systems are not so advanced. This paper suggests 3 possible solutions to implement the run-time configuration intrinsic EHW system: FPGA-based Run-Time Configuration system, JBits-based Run-Time Configuration system and Multi-board functional-level Run-Time Configuration system. The main characteristic of the proposed architectures is that they are implemented on Field Programmable Gate Array. A comparison of proposed solutions demonstrates that multi-board functional-level run-time configuration is superior in terms of scalability, flexibility and the implementation easiness.

Keywords: Evolvable hardware, evolutionary computation, FPGA systems.

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Authors: B. Bagheri Nakhjavanlo, T. J. Ellis, P. Raoofi, J. Dehmeshki

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This paper presents a customized deformable model for the segmentation of abdominal and thoracic aortic aneurysms in CTA datasets. An important challenge in reliably detecting aortic aneurysm is the need to overcome problems associated with intensity inhomogeneities and image noise. Level sets are part of an important class of methods that utilize partial differential equations (PDEs) and have been extensively applied in image segmentation. A Gaussian kernel function in the level set formulation, which extracts the local intensity information, aids the suppression of noise in the extracted regions of interest and then guides the motion of the evolving contour for the detection of weak boundaries. The speed of curve evolution has been significantly improved with a resulting decrease in segmentation time compared with previous implementations of level sets. The results indicate the method is more effective than other approaches in coping with intensity inhomogeneities.

Keywords: Abdominal and thoracic aortic aneurysms, intensityinhomogeneity, level sets, local fitting binary.

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Authors: O. M. Omar, A. M. Heniegal, G. D. Abd Elhameed, H. A. Mohamadien

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Local steel slag is produced as a by-product during the oxidation of steel pellets in an electric arc furnace. Using local steel slag waste as a hundred substitutes of crashed stone in construction materials would resolve the environmental problems caused by the large-scale depletion of the natural sources of crashed stone. This paper reports the experimental study to investigate the influence of a hundred replacement of crashed stone as a coarse aggregate with local steel slag, on the fresh and hardened geopolymer concrete properties. The investigation includes traditional testing of hardening concrete, for selected mixes of cement and geopolymer concrete. It was found that local steel slag as a coarse aggregate enhanced the slump test of the fresh state of cement and geopolymer concretes. Nevertheless, the unit weight of concretes was affected. Meanwhile, the good performance was observed when fly ash used as geopolymer concrete based.

Keywords: Geopolymer, molarity, steel slag, sodium hydroxide, sodium silicate.

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Authors: Dosun Shin, Assegid Kidane, Pavan Turaga

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This research project brings together experts in multiple disciplines to bring product design, sensor design, algorithms, and health intervention studies to develop a product and system that helps reduce the amount of time sitting at the workplace. This paper illustrates ongoing improvements to prototypes the research team developed in initial research; including working prototypes with a software application, which were developed and demonstrated for users. Additional modifications were made to improve functionality, aesthetics, and ease of use, which will be discussed in this paper. Extending on the foundations created in the initial phase, our approach sought to further improve the product by conducting additional human factor research, studying deficiencies in competitive products, testing various materials/forms, developing working prototypes, and obtaining feedback from additional potential users. The solution consisted of an aesthetically pleasing seat cover cushion that easily attaches to common office chairs found in most workplaces, ensuring that a wide variety of people can use the product. The product discreetly contains sensors that track when the user sits on their chair, sending information to a phone app that triggers reminders for users to stand up and move around after sitting for a set amount of time. This paper also presents the analyzed typical office aesthetics and selected materials, colors, and forms that complimented the working environment. Comfort and ease of use remained a high priority as the design team sought to provide a product and system that integrated into the workplace. As the research team continues to test, improve, and implement this solution for the sedentary workplace, the team seeks to create a viable product that acts as an impetus for a more active workday and lifestyle, further decreasing the proliferation of chronic disease and health issues for sedentary working people. This paper illustrates in detail the processes of engineering, product design, methodology, and testing results.

Keywords: Anti-sedentary work behavior, new product development, sensor design, health intervention studies.

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Authors: A. V. Sai Balasubramanian, N. Ravi Shankar, S. Subbaraman, R. Rengaraj

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One of the major cause of eye strain and other problems caused while watching television is the relative illumination between the screen and its surrounding. This can be overcome by adjusting the brightness of the screen with respect to the surrounding light. A controller based on fuzzy logic is proposed in this paper. The fuzzy controller takes in the intensity of light surrounding the screen and the present brightness of the screen as input. The output of the fuzzy controller is the grid voltage corresponding to the required brightness. This voltage is given to CRT and brightness is controller dynamically. For the given test system data, different de-fuzzifier methods have been implemented and the results are compared. In order to validate the effectiveness of the proposed approach, a fuzzy controller has been designed by obtaining a test data from a real time system. The simulations are performed in MATLAB and are verified with standard system data. The proposed approach can be implemented for real time applications.

Keywords: Fuzzy controller, Grid voltage

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Authors: O. Ikpotokin

Abstract:

In any production process, every product is aimed to attain a certain standard, but the presence of assignable cause of variability affects our process, thereby leading to low quality of product. The ability to identify and remove this type of variability reduces its overall effect, thereby improving the quality of the product. In case of a univariate control chart signal, it is easy to detect the problem and give a solution since it is related to a single quality characteristic. However, the problems involved in the use of multivariate control chart are the violation of multivariate normal assumption and the difficulty in identifying the quality characteristic(s) that resulted in the out of control signals. The purpose of this paper is to examine the use of non-parametric control chart (the bootstrap approach) for obtaining control limit to overcome the problem of multivariate distributional assumption and the p-value method for detecting out of control signals. Results from a performance study show that the proposed bootstrap method enables the setting of control limit that can enhance the detection of out of control signals when compared, while the p-value method also enhanced in identifying out of control variables.

Keywords: Bootstrap control limit, p-value method, out-of-control signals, p-value, quality characteristics.

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Authors: G. Schuh, A. Kampker, A. Hoeschen, T. Jasinski

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Today-s manufacturing companies are facing multiple and dynamic customer-supplier-relationships embedded in nonhierarchical production networks. This complex environment leads to problems with delivery reliability and wasteful turbulences throughout the entire network. This paper describes an operational model based on a theoretical framework which improves delivery reliability of each individual customer-supplier-relationship within non-hierarchical production networks of the European machinery and equipment industry. By developing a non-centralized coordination mechanism based on determining the value of delivery reliability and derivation of an incentive system for suppliers the number of in time deliveries can be increased and thus the turbulences in the production network smoothened. Comparable to an electronic stock exchange the coordination mechanism will transform the manual and nontransparent process of determining penalties for delivery delays into an automated and transparent market mechanism creating delivery reliability.

Keywords: delivery reliability, machinery and equipmentindustry, non-hierarchical production networks, supply chainmanagement

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Authors: Turki M. Habeebullah, Atef M. F. Mohammed, Essam A. Morsy

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In recent decades, particulate matter (PM10) have received much attention due to its potential adverse health impact and the subsequent need to better control or regulate these pollutants. The aim of this paper is focused on study risk assessment of PM10 in four different districts (Shebikah, Masfalah, Aziziyah, Awali) in Makkah, Saudi Arabia during the period from 1 Ramadan 1434 AH - 27 Safar 1435 AH. Samples were collected by using Low Volume Sampler (LVS Low Volume Sampler) device and filtration method for estimating the total concentration of PM10. The study indicated that the mean PM10 concentrations were 254.6 (186.1 - 343.2) μg/m3 in Shebikah, 184.9 (145.6 - 271.4) μg/m3 in Masfalah, 162.4 (92.4-253.8) μg/m3 in Aziziyah, and 56.0 (44.5 - 119.8) μg/m3 in Awali. These values did not exceed the permissible limits in PME (340 μg/m3 as daily average). Furthermore, health assessment is carried out using AirQ2.2.3 model to estimate the number of hospital admissions due to respiratory diseases. The cumulative number of cases per 100,000 were 1534 (18-3050 case), which lower than that recorded in the United States, Malaysia. The concentration response coefficient was 0.49 (95% CI 0.05 - 0.70) per 10 μg/m3 increase of PM10.

Keywords: Air pollution, Respiratory diseases, AirQ2.2.3, Makkah.

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Authors: Costa, E.S., Borges, E.N.M., Afonso, M.M.

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The modeling of sound radiation is of fundamental importance for understanding the propagation of acoustic waves and, consequently, develop mechanisms for reducing acoustic noise. The propagation of acoustic waves, are involved in various phenomena such as radiation, absorption, transmission and reflection. The radiation is studied through the linear equation of the acoustic wave that is obtained through the equation for the Conservation of Momentum, equation of State and Continuity. From these equations, is the Helmholtz differential equation that describes the problem of acoustic radiation. In this paper we obtained the solution of the Helmholtz differential equation for an infinite cylinder in a pulsating through free and homogeneous. The analytical solution is implemented and the results are compared with the literature. A numerical formulation for this problem is obtained using the Boundary Element Method (BEM). This method has great power for solving certain acoustical problems in open field, compared to differential methods. BEM reduces the size of the problem, thereby simplifying the input data to be worked and reducing the computational time used.

Keywords: Acoustic radiation, boundary element

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Authors: Qin Wei

Abstract:

There has been an increased number of immigrants arriving in Canada and a concurrent rise in the number of immigrant youth suffering from drug abuse. Immigrant youths’ drug abuse has become a significant social and public health concern for researchers. This paper explores the nature of immigrant youths’ drug abuse by examining the factors influencing the onset of substance misuse, the barriers that discourage youth to seek out treatment, and how to resolve addictions amidst immigrant youth. Findings demonstrate that diminished parental supervision, acculturation challenges, peer conformity, discrimination, and ethnic marginalization are all significant factors influencing youth to use drugs as an outlet for their pain, while culturally incompetent care and fear of family and culture-based addiction stigma act as barriers discouraging youth from seeking out addiction support. To resolve addiction challenges amidst immigrant youth, future research should focus on promoting and implementing culturally sensitive practices and psychoeducational initiatives into immigrant communities and within public health policies.

Keywords: Approaches, barriers, drug abuse, Canada, immigrant youth.

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Authors: Phalaunnaphat Siriwongs

Abstract:

The classroom of the 21st century is an ever changing forum for new and innovative thoughts and ideas. With increasing technology and opportunity, students have rapid access to information that only decades ago would have taken weeks to obtain. Unfortunately, new techniques and technology is not a cure for the fundamental problems that have plagued the classroom ever since education was established. Class size has been an issue long debated in academia. While it is difficult to pin point an exact number, it is clear that in this case more does not mean better. By looking into the success and pitfalls of classroom size the true advantages of smaller classes will become clear. Previously, one class was comprised of 50 students. Being seventeen and eighteen-year-old students, sometimes it was quite difficult for them to stay focused. To help them understand and gain much knowledge, a researcher introduced “The Theory of Multiple Intelligence” and this, in fact, enabled students to learn according to their own learning preferences no matter how they were being taught. In this lesson, the researcher designed a cycle of learning activities involving all intelligences so that everyone had equal opportunities to learn.

Keywords: Multiple Intelligences, role play, performance assessment, formative assessment.

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Authors: Aziza Benaboud, Alfred Rufer

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In this paper the authors propose a flexible electronic solution, to improve the energetic efficiency of a thermo plant. This is achieved by replacing the mechanical gear box, placed traditionally between a gas turbine and a synchronous generator; by a power electronic converter. After reminding problematic of gear boxes and interest of a proposed electronic solution in high power plants, the authors describe a new control strategy for an indirect frequency converter, which is characterized by its high efficiency due to the use of SWM: Square Wave Modulation. The main advantage of this mode is the quasi absence of switching losses. A control method is also proposed to resolve some problems incurred by using square wave modulation, in particular to reduce the harmonics distortion of the output inverter voltage and current. Simulation examples as well as experimental results are included.

Keywords: Angle shift, high efficiency, indirect converter, gas turbine, NPC three level converter, square wave modulation SWM, switching angle.

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Authors: Y. B. Galerkin, E. Y. Popova, K. V. Soldatova

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There is an evident trend to elevate pressure ratio of a single stage of a turbo compressors - axial compressors in particular. Whilst there was an opinion recently that a pressure ratio 1,9 was a reasonable limit, later appeared information on successful modeling tested of stages with pressure ratio up to 2,8. The authors recon that lack of information on high pressure stages makes actual a study of rational choice of design parameters before high supersonic flow problems solving. The computer program of an engineering type was developed. Below is presented a sample of its application to study possible parameters of the impeller of the stage with pressure ratio 3,0. Influence of two main design parameters on expected efficiency, periphery blade speed and flow structure is demonstrated. The results had lead to choose a variant for further analysis and improvement by CFD methods.

Keywords: Supersonic stage, impeller, efficiency, flow rate coefficient, work coefficient, loss coefficient, oblique shock, direct shock.

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Authors: Seyed Mohammad Reza Hosseini

Abstract:

The new institutional Economics helps generalization and expansion of new classic by adding the institution theories to Economic. It is clear that the appropriate institution is among the factors that lead to success in Economic programs. If the institutional are appropriate, the society will save the source and when we make use of time to apply the program, there will be welfare and average revenue product will also increase. In Economy, one should not expect the real manifestation of Economic programs only with a model for estimating and predicting rather institutions of the same purpose and along with production are needed to form the process of growth and development costs. In this research, the institution role in transaction costs, financial markets, distribution of revenue and capital and its influence on the process of growth and development are investigated so that handicaps and problems of Iran Economic Institutions can be recognized. In other words, incapability, non productivity and ambiguity of the institution in Iran Economic are some of the factors that handicap Economic growth and development. For example, Iran government as an important institution while having 20 ministries,83 organizations and 60 years of programming could not go along the growth and development but why?

Keywords: Institution, New institutional economics, Transaction costs.

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Authors: Lazim Abdullah, N orhanadiah Zam

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Increasing number of vehicles and lack of awareness among road users may lead to road accidents. However no specific literature was found to rank vehicles involved in accidents based on fuzzy variables of road users. This paper proposes a ranking of four selected motor vehicles involved in road accidents. Human and non-human factors that normally linked with road accidents are considered for ranking. The imprecision or vagueness inherent in the subjective assessment of the experts has led the application of fuzzy sets theory to deal with ranking problems. Data in form of linguistic variables were collected from three authorised personnel of three Malaysian Government agencies. The Multi Criteria Decision Making, fuzzy TOPSIS was applied in computational procedures. From the analysis, it shows that motorcycles vehicles yielded the highest closeness coefficient at 0.6225. A ranking can be drawn using the magnitude of closeness coefficient. It was indicated that the motorcycles recorded the first rank.

Keywords: Road accidents, decision making, closeness coefficient, fuzzy number

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Authors: Hong Bae Kim, Chang Ho Hur

Abstract:

Many governments have tried to reduce CO₂ emissions which are believed to be the main cause for global warming. The deployment of electric automobiles is regarded as an effective way to reduce CO₂ emissions. The Korean government has planned to deploy about 200,000 electric automobiles. The policy for the deployment of electric automobiles aims at not only decreasing gasoline consumption but also increasing electricity production. However, if an electricity consuming regions is not consistent with an electricity producing region, the policy generates environmental problems between regions. Hence, this paper has established the energy multi-region input-output model to specifically analyze the impacts of the deployment of electric automobiles on regional energy consumption and CO₂ emissions. Finally, the paper suggests policy directions regarding the deployment of electric automobiles.

Keywords: Electric automobiles, CO2 emissions, regional imbalances in electricity production and consumption, energy multi-region input-output model.

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Authors: Witcha Chimphlee, Abdul Hanan Abdullah, Mohd Noor Md Sap, Siriporn Chimphlee, Surat Srinoy

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It is important problems to increase the detection rates and reduce false positive rates in Intrusion Detection System (IDS). Although preventative techniques such as access control and authentication attempt to prevent intruders, these can fail, and as a second line of defence, intrusion detection has been introduced. Rare events are events that occur very infrequently, detection of rare events is a common problem in many domains. In this paper we propose an intrusion detection method that combines Rough set and Fuzzy Clustering. Rough set has to decrease the amount of data and get rid of redundancy. Fuzzy c-means clustering allow objects to belong to several clusters simultaneously, with different degrees of membership. Our approach allows us to recognize not only known attacks but also to detect suspicious activity that may be the result of a new, unknown attack. The experimental results on Knowledge Discovery and Data Mining-(KDDCup 1999) Dataset show that the method is efficient and practical for intrusion detection systems.

Keywords: Network and security, intrusion detection, fuzzy cmeans, rough set.

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Authors: J. George, M. Al Mutairi, W. Aljuryyad, A. Alhussanan, A. Alkashan, T. Aldoghiri, Z. Alamari, A. Albakr

Abstract:

Introduction: Students make plans for their career and are keen in exploring options of employment in those carriers. They make their employment choice based on their desires and preferences. This study aims to identify if students of King Saud Bin Abdulaziz for Health Sciences, College of Applied Medical Sciences after obtaining appropriate education prefer to work as clinicians, university faculty, or full-time researchers. There are limited studies in Saudi Arabia exploring the university student’s employment choices and preferences. This study would help employers to build the required job positions and prevent misleading employers from opening undesired positions in the job market. Methodology: The study included 394 students from third and fourth years both male and female among the eighth programs of college of applied medical sciences, King Saud Bin Abdulaziz University for Health Sciences (KSAU-HS), Riyadh campus. A prospective quantitative cross-sectional study was conducted; data were collected by distributing a seven item questionnaire and analyzed using SPSS. Results: Among the participants, 358 (90.9%) of them chose one of the three listed career choices, 263 (66.8%) decided to work as hospital staff after their education, 75 students (19.0%) chose to work as a faculty member in a university after obtaining appropriate degree, 20 students (5.1%) preferred to work as full-time researcher after obtaining appropriate degree, the remaining 36 students (9.1%) had different career goals, such as obtaining a master degree after graduating, to obtain a bachelor of medicine and bachelor in surgery degree, and working in the private sector. The most recurrent reason behind the participants' choice was "career goal", where 276 (70.1%) chose it as a reason. Conclusion: The findings of the study showed that most student’s preferred to work in hospitals as clinicians, followed by choice of working as a faculty in a university, the least choice was to be working as full-time researchers.

Keywords: College of Applied Medical Sciences, employment ambitions, graduating students, King Saud bin Abdulaziz University for Health Sciences.

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Authors: M. Kasusse, M. Rosette, E. Burke, C. Mwangi, R. Batamwita, N. Tumwesigye, S. Aisu

Abstract:

A cross-sectional survey to ascertain the capacity of laboratory persons in using ICTs was conducted in 15 Ugandan districts (July-August 2013). A self-administered questionnaire served as data collection tool, interview guide and observation checklist. 69 questionnaires were filled, 12 interviews conducted, 45 HC observed. SPSS statistics 17.0 and SAS 9.2 software were used for entry and analyses. 69.35% of participants find it difficult to access a computer at work. Of the 30.65% who find it easy to access a computer at work, a significant 21.05% spend 0 hours on a computer daily. 60% of the participants cannot access internet at work. Of the 40% who have internet at work, a significant 20% lack email address but 20% weekly read emails weekly and 48% daily. It is viable/feasible to pilot informatics projects as strategies to build bridges develop skills for e-health landscape in laboratory services with a bigger financial muscle.

Keywords: ICT Behavior, Clinical Laboratory persons, Sub-Saharan Africa, Uganda.

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Authors: Zhenhuan Zhu, David Mulvaney, Vassilios Chouliaras

Abstract:

A new genetic algorithm, termed the 'optimum individual monogenetic genetic algorithm' (OIMGA), is presented whose properties have been deliberately designed to be well suited to hardware implementation. Specific design criteria were to ensure fast access to the individuals in the population, to keep the required silicon area for hardware implementation to a minimum and to incorporate flexibility in the structure for the targeting of a range of applications. The first two criteria are met by retaining only the current optimum individual, thereby guaranteeing a small memory requirement that can easily be stored in fast on-chip memory. Also, OIMGA can be easily reconfigured to allow the investigation of problems that normally warrant either large GA populations or individuals many genes in length. Local convergence is achieved in OIMGA by retaining elite individuals, while population diversity is ensured by continually searching for the best individuals in fresh regions of the search space. The results given in this paper demonstrate that both the performance of OIMGA and its convergence time are superior to those of a range of existing hardware GA implementations.

Keywords: Genetic algorithms, genetic hardware, machinelearning.

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